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Ambulatory impairments; Machine learning; Multiple sclerosis Deficiencias ambulatorias; Aprendizaje automático; Esclerosis múltiple Deficiències ambulatòries; Aprenentatge automàtic; Esclerosi múltiple Abstract Background and objectives Multiple sclerosis (MS) is a progressive inflammatory and neurodegenerative disease of the central nervous system affecting over 2.5 million people globally. In-clinic six-minute walk test (6MWT) is a widely used objective measure to evaluate the progression of MS. Yet, it has limitations such as the need for a clinical visit and a proper walkway. The widespread use of wearable devices capable of depicting patients’ activity profiles has the potential to assess the level of MS-induced disability in free-living conditions. Methods In this work, we extracted 96 features in different temporal granularities (from minute-level to day-level) from wearable data and explored their utility in estimating 6MWT scores in a European (Italy, Spain, and Denmark) MS cohort of 337 participants over an average of 10 months’ duration. We combined these features with participants’ demographics using three regression models including elastic net, gradient boosted trees and random forest. In addition, we quantified the individual feature's contribution using feature importance in these regression models, linear mixed-effects models, generalized estimating equations, and correlation-based feature selection (CFS). Results The results showed promising estimation performance with R2 of 0.30, which was derived using random forest after CFS. This model was able to distinguish the participants with low disability from those with high disability. Furthermore, we observed that the minute-level (≤ 8 minutes) step count, particularly those capturing the upper end of the step count distribution, had a stronger association with 6MWT. The use of a walking aid was indicative of ambulatory function measured through 6MWT. Conclusions This study demonstrates the utility of wearables devices in assessing ambulatory impairments in people with MS in free-living conditions and provides a basis for future investigation into the clinical relevance. The RADAR-CNS project has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No 115902. This Joint Undertaking receives support from the European Union's Horizon 2020 research and innovation programme and EFPIA, www.imi.europa.eu. This paper reflects the views of the RADAR-CNS consortium and neither IMI nor the European Union and EFPIA are liable for any use that may be made of the information contained herein. The funding body have not been involved in the design of the study, the collection or analysis of data, or the interpretation of data. RJBD is supported by the following: (1) NIHR Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London, London, UK; (2) Health Data Research UK, which is funded by the UK Medical Research Council, Engineering and Physical Sciences Research Council, Economic and Social Research Council, Department of Health and Social Care (England), Chief Scientist Office of the Scottish Government Health and Social Care Directorates, Health and Social Care Research and Development Division (Welsh Government), Public Health Agency (Northern Ireland), British Heart Foundation and Wellcome Trust; (3) The BigData@Heart Consortium, funded by the Innovative Medicines Initiative-2 Joint Undertaking under grant agreement No. 116074. This Joint Undertaking receives support from the European Union's Horizon 2020 research and innovation programme and EFPIA; it is chaired by DE Grobbee and SD Anker, partnering with 20 academic and industry partners and ESC; (4) the National Institute for Health Research University College London Hospitals Biomedical Research Centre; (5) the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London; (6) the UK Research and Innovation London Medical Imaging & Artificial Intelligence Centre for Value Based Healthcare; (7) the National Institute for Health Research (NIHR) Applied Research Collaboration South London (NIHR ARC South London) at King's College Hospital NHS Foundation Trust.

This review outlines the feasibility of oral lipid-based targeted delivery of drugs to the brain, including permeation of the central nervous system's (CNS) protective blood-brain barrier (BBB). The structure of the BBB and disruption caused by varying disease states highlights the need for disease-specific approaches to alter permeation. Disruption during disease state, and the effects of certain molecules on the barrier, demonstrate the possibility of exploiting such BBB disruption for drug delivery. Many administration methods can be used to target the brain, but oral administration is considered ideal for chronic, long-term illnesses. Several lipids that have been shown to facilitate drug delivery into the brain after systemic administration, but could also be delivered orally, are discussed, including oleic acid, triolein, alkylglycerol, and conjugates of linoleic and myristic acids. Current data reveal the potential for the use of such lipids as part of oral formulations for delivery to the brain by reaching sufficient plasma levels after administration to increase the permeability of the BBB. However, gaps in the literature remain regarding the concentrations and form of most lipids required to produce the desired effects. The use of lipids via oral delivery for brain targeting has not been investigated thoroughly enough to determine with certainty if similar permeability-enhancing effects would be observed as for parenteral administration. In conclusion, further research to fill research gaps is needed, but the limited evidence suggests that oral lipid-based drug delivery for brain targeting is potentially feasible.

Shape memory alloys were generally produced by casting but powder metallurgy has fast become an alternative method for producing shape memory alloys, specifically NiTi. Powder metallurgy became a popular method due to its ability to avoid the problems of segregation and excessive grain growth associated with casting and it allows for better control over the composition of NiTi alloy and can therefore control the transformation temperature and in turn the alloys unique shape memory and superelastic properties. Spark plasma sintering has emerged as the most efficient powder metallurgical method of melting binary and ternary NiTi.

Cyclic calcination/carbonation, carried out in fluidized bed chemical looping systems, can be used to provide continuous streams of gas in which molar concentrations of carbon dioxide reach 95% or more. Operating at elevated pressures has significant advantages in reducing the required reactor size, increasing reaction rates, shifting the equilibrium of several key reactions in a positive direction, and improving fluidized bed hydrodynamics and heat/mass transfer rates. In gasification and reforming systems, CO 2 capture can also enhance operation by shifting the equilibrium of key reactions in a positive direction. These advantages are offset in part by the extra complexity of feeding particles into high-pressure reactors and probable increases in sorbent attrition. The effects of increasing the operating pressure are summarized for fluidized beds in which calcium looping is operating for the capture of CO 2 . The chapter also compares pressure swing calcination/carbonation cycling with temperature swing based on experimental data and practical considerations. It is shown that pressure swing has advantages in terms of sorbent performance and energy usage associated with swinging back and forth between calcination and carbonation conditions. However, the temperature may need to be so high that substantial sintering of the sorbent is caused, and the release of pressure may augment sorbent attrition. The positive potential of high-pressure operation and pressure swing are such that further research and demonstration of these technologies is warranted for CO 2 capture in looping systems.